Use of the market approach in the appraisal of a medical practice is a contentious issue among valuators. The size and quality of available datasets (or lack thereof) are the most common issues cited in the rejection of this approach. I feel the market approach can be an effective tool as a “sanity check” or even a standalone method in the absence of other relevant methods. It all depends on one’s understanding of the different market data sets and the skill used in making appropriate adjustments.
Medical Practice Valuation
Most market data sets report varying degrees of financial information and some detail regarding the medical specialty and nature of the business. However, clinical details, providers and FTE levels, work RVUs and productivity, payer mix and other information is not available. This can make it difficult to benchmark non financial metrics. Valuators often reject the market approach because of the lack of additional comparable information but they may be doing so prematurely. Market data can still have validity but needs to be adjusted and qualified in order to be used appropriately. I commonly use data from multiple market surveys and will explain below how I treat the information and its limitations.
What Data to Use
A number of published data sources exist which aggregate transactions of closely held medical practices and healthcare facilities. Because these are closely held businesses, not all pertinent details may be reported. Additional gaps exist in the way that the surveys collect the information from respondents. In Part 1 of this article I will cover some of these data sources and how I use them.
The Goodwill Registry
The goodwill registry (“GWR”) is a survey of transactions compiled from responses by medical practice brokers, appraisers, accountants and attorneys. The GWR suffers from the same problem that most of the surveys do in that it does not report clinical and operational information. Nevertheless it has a large number of transactions for most of the major medical specialties and proves to be a helpful tool.
My primary complaint of the GWR is the reporting of “goodwill”. The definition of goodwill and how it is reported to the survey is problematic in my opinion. It is impossible to tell whether “goodwill” has been separately measured or whether it is merely reported for purchase price allocation. This makes it difficult to rely on the data to come up with goodwill comparisons. The survey also seems to commingle goodwill with other intangible asset classes. I do not rely on goodwill figures and instead use the earnings and revenue figures.
The two area of the survey that I do rely on are the price to earnings and price to revenue ratios. Again, the use of these ratios requires careful applications. “Earnings” as reported in the survey is most closely associated with the business broker term “Sellers Discretionary Earnings” or SDE. Therefore if you are making an earnings comparison it is important to add back the salaries and discretionary expenses of owner/operator physicians as well as non cash items. “Revenue” is generally considered to be net collections, usually reported on a cash basis considering the size of most entities in the survey. “Price” is considered to be on an asset basis excluding current assets and liabilities. As you can see, the way data is reported can have an immense affect on how the valuators calculates and adjusts asset, equity, or enterprise value. When I did work as a medical practice broker I submitted hundreds of transactions to the GWR and have confidence in the limited data they do provide.
Pratt’s Stats does a much better job in reporting financials but its data in the hands of an untrained valuator is worthless. Pratt contains numerous strategic deals, public entity buyers, real estate, unusual deal terms and non cash considerations among other things. Without careful screening of the data it can be easy to end up with inaccurate results. Prices are reported as Market Value of Invested Capital (“MVIC”) and also needs to be adjusted to get the proper result. What I like most about Pratt’s Stats is that balance sheet information and other stats are available which other surveys don’t provide. One major limitation which Pratt’s Stats shares with the other surveys is the limited number of transactions present in the healthcare arena.
The IBA database is nice to use but also lacks sufficient healthcare transactions. The ones it does have tend to be quite old and have limited description of the medical specialty. I use this data rarely, though I do like the DMDM metrics produced by IBA in excel format when I do use it.
Other data source do exist but I find them limited in their capability. GWR, Pratt, and IBA are the main ones I end up using as a market-based sanity check
Rules of Thumb
Another topic which arises when discussing the market approach is the use of rules of thumb. I am not opposed to their use as a sanity check but I don’t believe they constitute a defensible valuation method. Rules of thumb may have been more accurate during times where the healthcare environment was more homogeneous. Differences in payor mix, reimbursement, and regional market dynamics have changed all of that. That said, some markets have more consistently observable market trends which make rules of thumb acceptable to rely on a sanity check. In my market in Southern California for example, small primary care practices tend to sell for 1-1.5x discretionary earnings. While this may be a fairly consistent trend I would never use it as a method in a valuation report.
Generally if you’ve done enough work in a particular market you should be able to determine if a market multiple is accurate or not. Also, if you have used other methods which produce divergent values from your market approach then you might need to reconsider the other methods and their inputs. Generally I am a proponent of the use of market information in the appraisal of a medical practice so long its done properly. In Part 2 of this article I will discuss the mechanics of regression analysis and market multiple analysis.1